Principal Data Scientist

1 day ago

New York NY United States Capital One Full time

Locations: VA - McLean, United States of America, McLean, Virginia

Principal Data Scientist

Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988 Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.

As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

Team Description

The PACMAN team builds the machine learning models that help ensure easy and secure management of data and privileges. We work with multiple teams to understand difficult problems, explore rich data sets and build complex ensemble models, deploying them on Capital One’s enterprise model platform. We use Python and open-source packages like PyTorch.

Role Description

In this role, you will:

  1. Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love.

  2. Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data.

  3. Grapple with messy and incomplete data while getting creative with solutions to challenging problems.

  4. Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation.

  5. Flex your interpersonal skills to translate the complexity of your work into tangible business goals.

The Ideal Candidate is:

  1. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.

  2. Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.

  3. Statistically-minded. You’ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.

  4. A data guru. “Big data” doesn’t faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.

Basic Qualifications:

  1. Currently has, or is in the process of obtaining a Bachelor’s Degree plus 5 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus 3 years in data analytics, or currently has, or is in the process of obtaining PhD, with an expectation that required degree will be obtained on or before the scheduled start date.

  2. At least 1 year of experience in open source programming languages for large scale data analysis.

  3. At least 1 year of experience with machine learning.

  4. At least 1 year of experience with relational databases.

Preferred Qualifications:

  1. Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics).

  2. At least 1 year of experience working with AWS.

  3. At least 1 year of experience with SQL.

  4. At least 3 years of experience in Python, Scala, or R.

  5. At least 3 years of experience with machine learning (including neural networks, NLP).

  6. At least 3 years of experience with exploratory data analysis.

  7. At least 1 year of experience with probabilistic models or inferential statistics.

  8. Experience with LLMs or reinforcement learning is a plus.

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website .

This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace.

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